Automatic grouping based handling of similar photos

ABSTRACT

Technologies are described in conjunction with automatic grouping based handling of similar photos. According to some examples, similar photos maybe grouped as a group of people or person&#39;s image taken within a short time frame. Grouping of the photos may be based on a difference metric comparing facial features, background composition, and color composition. Among the group of photos, a representative image may be selected based on a quality threshold and displayed representing the entire group. Visual aids such as icons, text, and other elements may be used to indicate information associated with the grouped photos. Context based menus may be presented to allow users to select and handle the entire group or photos within the group seamlessly as the user handles other images within a photo viewing/handling user interface.

BACKGROUND

Smartphone or digital camera users may tend to photograph the samesubject or scene multiple times in order to capture a perfect shot.While some cameras may have an explicit “burst capture” mode, where manyshots may be captured sequentially in a short time frame, users maystill prefer tapping a normal shutter button over using this extra mode.However, users typically have to switch to a special mode to capturesuch photos and then view them. While some grouping features may beprovided, processing such as viewing, deleting, moving, etc. of thegrouped photos can be a cumbersome endeavor using conventionalapplications.

SUMMARY

This summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This summary is not intended to exclusively identify keyfeatures or essential features of the claimed subject matter, nor is itintended as an aid in determining the scope of the claimed subjectmatter.

Embodiments are directed to automatic grouping based handling of similarphotos, a plurality of photos taken within a predefined period of timeor of a similar scene may be received at a photo service. The photoservice may analyze the plurality of photos based on a capture time,facial features, a background composition, and a color composition, andgroup a subset of the plurality of photos as a stack based on applying athreshold to analysis results. The photo service may then select one ofthe photos in the stack as a representative photo based on a qualitythreshold, and provide the stack to be displayed in a collapsed formatwith the representative photo on top using one or more visual indicatorsassociated with the stack.

These and other features and advantages will be apparent from a readingof the following detailed description and a review of the associateddrawings. It is to be understood that both the foregoing generaldescription and the following detailed description are explanatory anddo not restrict aspects as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 includes an example network environment where a system forautomatically grouping based handling of similar photos may beimplemented;

FIG. 2 includes a conceptual diagram illustrating an example system oftwo distinct devices for automatic grouping based handling of similarphotos;

FIG. 3 includes an example photo service for automatic grouping basedhandling of similar photos;

FIG. 4 includes an example user interface associated with automaticgrouping based handling of similar photos;

FIG. 5 includes another example user interface associated with automaticgrouping based handling of similar photos;

FIG. 6 is a networked environment, where a system according toembodiments may be implemented;

FIG. 7 is a block diagram of an example general purpose computingdevice, which may be used for automatic grouping based handling ofsimilar photos; and

FIG. 8 illustrates a logic flow diagram of a method for automaticgrouping based handling of similar photos.

DETAILED DESCRIPTION

As briefly described above, embodiments are directed to automaticgrouping based handling of similar photos. According to some examples,similar photos may be grouped as a group of people or person's imagetaken within a short time frame. Grouping of the photos may be based ona difference metric comparing facial features, background composition,and color composition. Among the group of photos, a representative imagemay be selected based on a quality threshold and displayed representingthe entire group. Visual aids such as icons, text, and other elementsmay be used to indicate information associated with the grouped photos.Context based menus may be presented to allow users to select and handlethe entire group or photos within the group seamlessly as the userhandles other images within a photo viewing/handling user interface.

In the following detailed description, references are made to theaccompanying drawings that form a part hereof, and in which are shown byway of illustrations, specific embodiments, or examples. These aspectsmay be combined, other aspects may be utilized, and structural changesmay be made without departing from the spirit or scope of the presentdisclosure. The following detailed description is therefore not to betaken in a limiting sense, and the scope of the present invention isdefined by the appended claims and their equivalents.

While some embodiments will be described in the general context ofprogram modules that execute in conjunction with an application programthat inns on an operating system on a personal computer, those skilledin the art will recognize that aspects may also be implemented incombination with other program modules.

Generally, program modules include routines, programs, components, datastructures, and other types of structures that perform particular tasksor implement particular abstract data types. Moreover, those skilled inthe art will appreciate that embodiments may be practiced with othercomputer system configurations, including hand-held devices,multiprocessor systems, microprocessor-based or programmable consumerelectronics, minicomputers, mainframe computers, and comparablecomputing devices. Embodiments may also be practiced in distributedcomputing environments where tasks are performed by remote processingdevices that are linked through a communications network. In adistributed computing environment, program modules may be located inboth local and remote memory storage devices.

Some embodiments may be implemented as a computer-implemented process(method), a computing system, or as an article of manufacture, such as acomputer program product or computer readable media. The computerprogram product may be a computer storage medium readable by a computersystem and encoding a computer program that comprises instructions forcausing a computer or computing system to perform example process(es).The computer-readable storage medium is a computer-readable memorydevice. The computer-readable storage medium can for example beimplemented via one or more of a volatile computer memory, anon-volatile memory, a hard drive, a flash drive, a floppy disk, or acompact disk, and comparable hardware media.

Throughout this specification, the term “platform” may be a combinationof software and hardware components for automatic grouping basedhandling of similar photos. Examples of platforms include, but are notlimited to, a hosted service executed over a plurality of servers, anapplication executed on a single computing device, and comparablesystems. The term “server” generally refers to a computing deviceexecuting one or more software programs typically in a networkedenvironment. However, a server may also be implemented as a virtualserver (software programs) executed on one or more computing devicesviewed as a server on the network. More detail on these technologies andexample operations is provided below.

FIG. 1 includes an example network environment where a system forautomatic grouping based handling of similar photos may be implemented.

As illustrated in diagram 100, an example system may include adatacenter 112 hosting a cloud-based photo service 114 configured toprovide storage for, enable sharing of, and process photos that may becaptured by and accessed across multiple devices and users. Thedatacenter 112 may include one or more processing servers 116 configuredto execute the photo service 114, among other components. In someembodiments, at least one of the processing servers 116 may be operableto execute a processing module 118 of the photo service 114, where theprocessing module 118 may be integrated with the photo service 114. Thedatacenter 112 may also include one or more storage servers 120configured to manage one or more data stores comprising data associatedwith photos retained by the photo service 114 and/or processing module118. As described herein, the photo service 114 and/or processing module118 may be implemented as software, hardware, or combinations thereof.

In some embodiments, the photo service 114 may be configured tointeroperate with various applications to process photos capturedlocally on user associated devices. For example, as illustrated in thediagram 100, a user 104 may execute a thin (e.g., a web browser) or athick (e.g., a locally installed client application) version of anapplication 106 through the device 102 with which the photo service 114may be configured to integrate and interoperate with over one or morenetworks, such as network 110. The application 106 may be an applicationhosted by the photo service, such as a photo client, for example. Thedevice 102 may include a desktop computer, a laptop computer, a tabletcomputer, a vehicle mount computer, a smart phone, or a wearablecomputing device, among other similar devices. A communication interfacemay facilitate communication between the photo service 114 and theapplication 106 over the network 110.

In an example embodiment, the photo service 114 may be configured toreceive photos stored on local storage 108 of the device 102. Thereceived photos may be stored remotely at the photo service 114 withinthe storage servers 120, for example. Ssimilar photos may be grouped asa group of people or person's image taken within a short time frame.Grouping of the photos may be based on a difference metric comparingfacial features, background composition, and color composition. Amongthe group of photos, a representative image may be selected based on aquality threshold and displayed representing the entire group. Visualaids such as icons, text, and other elements may be used to indicateinformation associated with the grouped photos. Context based menus maybe presented to allow users to select and handle the entire group orphotos within the group seamlessly as the user handles other imageswithin a photo viewing/handling user interface. In one embodiment,configuration and/or processing options may be provided to the user 104through a user experience of the application 106 to enable selection andhandling of captured photos (see FIGS. 4,5).

Some of the actions and/or processes described herein have beenillustrated from the perspective of a server (for example, theprocessing servers 116 configured to execute the photo service), howeverthe same actions may be performed similarly by a client (for example,the application 106), among other entities. Additionally, some of theactions and/or processes described herein have been illustrated from theperspective of the client, however the same actions may be performedsimilarly by the server.

Technical advantages of a system according to embodiments may includeenhanced user interaction in processing and viewing captured images,reduced bandwidth in sharing and storing grouped photos, and reducedprocessing resource usage by allowing context based actions to beperformed on individual photos or groups instead of having a user todeal with a large number of similar photos.

Embodiments, as described herein, address a need that arises from verylarge scale of operations created by software-based services that cannotbe managed by humans. The actions/operations described herein are not amere use of a computer, but address results of a system that is a directconsequence of software used as a service offered in conjunction withlarge numbers of devices and users storing and/or sharing content bothlocally at client devices and remotely at cloud-based storage services.

FIG. 2 includes a conceptual diagram illustrating an example system oftwo distinct devices for automatic grouping based handling of similarphotos.

As shown in a diagram 200, a user 206 may capture images using a camera202. The images may be transmitted to a computing device 204 directly(214) (e.g., via wired or wireless communication such as Bluetooth,infrared, or similar communication techniques) or over one or morenetworks 210 (network communication 212). Thus, the user 206 may viewand process the captured images on the camera 202 or at the computingdevice 204, for example, using a photo processing application.

In some embodiments, photos may be grouped as discussed above andtransmission to the computing device may be based on the type ofconnection. For example, if a broadband communication channel isavailable, all photos in a group may be transmitted, whereas if thecommunication bandwidth is limited or metered (e.g., cellular), only therepresentative photo may be transmitted. Thus, in some cases, someprocessing may be performed at the camera 202 and other processing maybe performed at the computing device 204.

In one example embodiment, the representative photo (e.g., best quality)may be transmitted to the computing device initially. If the userindicates they want to perform an action on one or more individualphotos of the group, the rest of the images from the group may betransmitted to the computing device 204. Similar approaches may beimplemented when the user shares grouped photos with other users.

FIG. 3 includes an example photo service for automatic grouping basedhandling of similar photos.

As shown in diagram 300, photos 310 along with their respective metadata312 such as time of capture, size, location, mode of capture (e.g.,burst mode, individual mode) may be captured by a capture device and/orapplication 314 and provided to a photo service 302. The photo service302 may include a processing module 304, which in turn may include ananalyzer engine 306 and an organizer engine 308. Organized photos 316may be provided to a viewing device or application 318 by the photoservice 302.

The photo service 302 and/or the capture device and/or application 314may use facial recognition/analysis, time of capture, location ofcapture, and/or color/background composition to determine grouping.Images taken within a short rime frame of the same person or persons atthe same location may be grouped together as a stack. Thus, a relativelylarge number of photos may be captured and a best quality imagedesignated as representative. A user may then share/store the entiregroup, the representative, or a subset of the group. The viewing deviceor application 318 may display the stack as a single entity avoidingclutter and confusion in viewing or handling the photos along withothers that may already be stored.

The “near-duplicate” images are typically taken where the user's intentmay be to capture a single, high quality image but instead may havetaken multiple photos to insure that at least one is not blurry or allsubjects are looking their best. Instead of having to remember to turnon a special mode, the user may shoot just the way he/she is used to,and let the photo service 302 to recognize the bursts automatically,electing a representative shot, for example, with open eyes and smilingfaces as the “top” image to display in the grid views. Thus, incapturing the photos, the user may not have to switch to a “burst” or“group” mode. They may take photos as they are accustomed to, and thephotos may be grouped automatically after the capture.

FIG. 4 includes an example user interface associated with automaticgrouping based handling of similar photos.

As shown in the user, interlace 402 of diagram 400, grouped or stackedphotos may be presented in a photo viewing mode in a collapsed manner toavoid cluttering the user interface with a large number of similarphotos. A representative photo 410 (top photo) may be displayed alongwith other (not belonging to the group) photos 404. Further unrelatedphotos 408 may also be displayed in rows, for example, in a grid view.The group may be indicated through visual indicators 414 such as icons,text, and other elements (e.g., highlighting or similar graphical schemeon the representative photo 410). Upon an action on the representativephoto 410 such as a tap or similar selection action, the group may beexpanded. For example, the photos 406 in the group may be displayed inon additional row by pushing the further unrelated photos 408 down.Among the photos 406 of the group, the representative photo 412 may bedisplayed directly under the group placeholder thumbnail (representativephoto 410). In another example, the group may open with therepresentative photo centered in a mobile user interface.

When iterating, both the group affordance and group strip may pan withthe flip view item. Once an open group is fully out of view, the groupshould close back (collapse) automatically to only display therepresentative photo again. The photo viewer may be configured to alsorotate into landscape mode. Like in portrait mode, application barbuttons (command objects) may swap from the general photo commands tothe group specific ones after iteration completes. Thus, the userinterface may switch between a group command bar displaying commandsrelated to operations on the group and a photo viewing command bardisplaying generic photo viewing commands depending on which group mode(collapsed or expanded) is on.

A photo similarity determination that uses a difference metric based on,for example, summing the red-blue-green (RGB) channels for each pixel ofan image and comparing it with another image via Root Mean Square (thevalue may be normalized, for example, from 0.0-1.0 and used as adifference metric). The threshold for including a photo in a group orstack may be based on tuning for high precision from user data. Forgroup shots, photos may be detected where the people in the photo aresmiling and have open eyes, for example.

The photo capture device, a digital camera or a smart phone camera, maycapture photos in an automatic or manual group capture mode, wherepressing a button once may result in a predefined number of photos beingcaptured of the same scene. In other examples, the user may be enabledto press the button and photos may be captured as long as the user keepsthe button pressed. In either case, the photos may be grouped, arepresentative photo selected, and group processing capabilitiesdiscussed herein may be provided automatically to the captured photossuch that the user does not have to identify manually photos to begrouped.

FIG. 5 includes another example user interface associated with automaticgrouping based handling of similar photos.

As shown in diagram 500, context based command menus may be provideddepending on which group mode (collapsed or expanded) is selected. Theavailable commands may be provided in a command bar at a fixed locationon the user interface or as dynamically located pop-up menus. In theexample illustration, the pop-up menu 506 may include group-specificcommands such as unstack (dissolve the group into individual photos),delete all, edit (group), share (representative photo), share all, oradd to album. The pop-up menu 506 may be displayed upon selection 504 orindication of interest (e.g., hovering on) the collapsed group item(thumbnail 502 of representative photo).

In some embodiments, the user may be enabled to share the entire group,the representative photo, or selected photos in the group. In someapplications, users may be allowed to assign selected photos to albumsand view/store/share the albums. Similar to sharing the entire group,the representative photo, or selected photos in the group may beassigned to an album with a default behavior of the representative photobeing assigned to save storage space and network usage. If therepresentative photo or a selected photo in the group is assigned to analbum and changes are made to the group (e.g., representative photochanged or deleted), the photo assigned to the album may beautomatically changed too.

In another scenario, the pop-up menu 512 may include photo-specificcommands such as set as top (representative photo), unstack (dissolvethe group into individual photos), delete selected photo, edit (selectedphoto), share (selected photo), or add to album. The pop-up menu 512 maybe displayed upon selection 510 or indication of interest (e.g.,hovering on) the expanded group item (thumbnail 508 of selected photo).The commands, menus, and behavior illustrated and discussed inconjunction with FIG. 5 are for illustration purposes only and do notconstitute a limitation on embodiments. Other commands, menus, andbehavior may be implemented using the principles discussed herein.

The examples provided in FIGS. 1 through 5 are illustrated with specificsystems, services, applications, modules, and notifications. Embodimentsare not limited to environments according to these examples. Automaticgrouping based handling of similar photos may be implemented inenvironments employing fewer or additional systems, services,applications, engines, and user experience configurations. Furthermore,the example systems, services, applications, modules, and notificationsshown in FIG. 1 through 5 may be implemented in a similar manner withother values using the principles described herein.

FIG. 6 is a networked environment, where a system according toembodiments may be implemented. In addition to locally installedapplications (for example, photo application 106), a processing module118 may also be employed in conjunction with hosted applications andservices (for example, a photo service 114) that may be implemented viasoftware executed over one or more servers 606 or individual server 608,as illustrated in diagram 600. A hosted service or application maycommunicate with client applications on individual computing devicessuch as a handheld computer 601, a desktop computer 602, a laptopcomputer 603, a smart phone 604, a tablet computer (or slate), 605(‘client devices’) through network(s) 610 and control a user interfacepresented to users.

Client devices 601-605 are used to access the functionality provided bythe hosted service or application. One or more of the servers 606 orserver, 608 may be used to provide a variety of services as discussedabove. Relevant data may be stored in one or more data stores (e.g. datastore 614), which may be managed by any one of the servers 606 or bydatabase server 612.

Networks) 610 may comprise any topology of servers, clients, Internetservice providers, and communication media. A system according toembodiments may have a static or dynamic topology. Network(s) 610 mayinclude a secure network such as an enterprise network, an unsecurenetwork such as a wireless open network, or the Internet. Network(s) 610may also coordinate communication over other networks such as PSTN orcellular networks. Network(s) 610 provides communication between thenodes described herein. By way of example, and not limitation,network(s) 610 may include wireless media such as acoustic, RF, infraredand other wireless media.

Many other configurations of computing devices, applications, engines,data sources, and data distribution systems may be employed forautomatic grouping based handling of similar photos. Furthermore, thenetworked environments discussed in FIG. 6 are for illustration purposesonly. Embodiments are not limited to the example applications, engines,or processes.

FIG. 7 is a block diagram of on example general purpose computingdevice, which may be used for automatic grouping based handling ofsimilar photos.

For example, computing device 700 may be used as a server, desktopcomputer, portable computer, smart phone, special purpose computer, orsimilar device. In an example basic configuration 702, the computingdevice 700 may include one or more processors 704 and a system memory706. A memory bus 708 may be used for communicating between theprocessor 704 and the system memory 706. The basic configuration 702 isillustrated in FIG. 7 by those components within the inner dashed line.

Depending on the desired configuration, the processor 704 may be of anytype, including but not limited to a microprocessor (μP). amicrocontroller (μC), a digital signal processor (DSP), or anycombination thereof. The processor 704 may include one more levels ofcaching, such as a level cache memory 712, one or more processor cores714, and registers 716. The example processor cores 714 may (each)include an arithmetic logic unit (ALU), a floating point unit (FPU), adigital signal processing core (DSP Core), or any combination thereof.An example memory controller 718 may also be used with the processor 704or in some implementations the memory controller 718 may be an internalpart of the processor 704.

Depending on the desired configuration, the system memory 706 may be ofany type including but not limited to volatile memory (such as RAM),non-volatile memory (such as ROM, flash memory, etc.) or any combinationthereof. The system memory 706 may include an operating system 720, aphoto service 722, and program data 724. The photo service 722 mayinclude a processing module 726, which may be an integrated module ofthe photo service 722. The photo service 722 and/or processing module726 may be configured to receive, at the photo service 722, capturedphotos, group the photos automatically, select a representative photo,and provide handling/viewing features based on the grouping. The programdata 724 may include, among other data, photo data 728, as describedherein.

The computing device 700 may have additional features or functionality,and additional interfaces to facilitate communications between the basicconfiguration 702 and any desired devices and interfaces. For example, abus/interface controller 730 may be used to facilitate communicationsbetween the basic configuration 702 and one or more data storage devices732 via a storage interface bus 734. The data storage devices 732 may beone or more removable storage devices 736, one or more non-removablestorage devices 738, or a combination thereof. Examples of the removablestorage and the non-removable storage devices include magnetic diskdevices such as flexible disk drives and hard-disk drives (HDDs),optical disk drives such as compact disk (CD) drives or digitalversatile disk (DVD) drives, solid state drives (SSD), and tape drivesto name a few. Example computer storage media may include volatile andnonvolatile, removable and non-removable media implemented in any methodor technology for storage of information, such as computer readableinstructions, data structures, program modules, or other data.

The system memory 706, the removable storage devices 736 and thenon-removable storage devices 738 are examples of computer storagemedia. Computer storage media includes, but is not limited to, RAM, ROM,EEPROM, flash memory or other memory technology, CD-ROM, digitalversatile disks (DVDs), solid state drives, or other optical storage,magnetic cassettes, magnetic tape, magnetic disk storage or othermagnetic storage devices, or any other medium which may be used to storethe desired information and which may be accessed by the computingdevice 700. Any such computer storage media may be pan of the computingdevice 700.

The computing device 700 may also include an interface bus 740 forfacilitating communication from various interface devices (for example,one or more output devices 742, one or more peripheral interfaces 744,and one or more communication devices 746) to the basic configuration702 via the bus/interface controller 730. Some of the example outputdevices 742 include a graphics processing unit 748 and an audioprocessing unit 750, which may be configured to communicate to variousexternal devices such as a display or speakers via one or more A/V ports752. One or more example peripheral interfaces 744 may include a serialinterface controller 754 or a parallel interface controller 756, whichmay be configured to communicate with external devices such as inputdevices (for example, keyboard, mouse, pen, voice input device, touchinput device, etc.) or other peripheral devices (for example, printer,scanner, etc.) via one or more I/O ports 758. An example communicationdevice 746 includes a network controller 760, which may be arranged tofacilitate communications with one or more other computing devices 762over a network communication link via one or more communication ports764. The one or more other computing devices 762 may include servers,computing devices, and comparable devices.

The network communication link may be one example of a communicationmedia Communication media may typically be embodied by computer readableinstructions, data structures, program modules, or other data in amodulated data signal, such as a carrier wave or other transportmechanism, and may include any information delivery media. A “modulateddata signal” may be a signal that has one or more of its characteristicsset or changed in such a manner as to encode information in the signal.By way of example, and not limitation, communication media may includewired media such as a wired network or direct-wired connection, andwireless media such as acoustic, radio frequency (RF), microwave,infrared (IR) and other wireless media. The term computer readable mediaas used herein may include both storage media and communication media.

The computing device 700 may be implemented as a part of a generalpurpose or specialized server, mainframe, or similar computer thatincludes any of the above functions. The computing device 700 may alsobe implemented as a personal computer including both laptop computer andnon-laptop computer configurations.

Example embodiments may also include methods for automatic groupingbased handling of similar photos. These methods can be implemented inany number of ways, including the structures described herein. One suchway may be by machine operations, of devices of the type described inthe present disclosure. Another optional way may be for one or more ofthe individual operations of the methods to be performed in conjunctionwith one or more human operators performing some of the operations whileother operations may be performed by machines. These human operatorsneed not be collocated with each other, but each can be only with amachine that performs a portion of the program. In other embodiments,the human interaction can be automated such as by pre-selected criteriathat may be machine automated.

FIG. 8 illustrates a logic flow diagram of a method for automaticgrouping based handling of similar photos, according to embodiments.

Process 800 may be implemented on a computing device, server, or othersystem. An example system may include a server comprising acommunication interface to facilitate communication between a storageservice and one or more devices, a memory, and one or more processors.The processors may be configured to, in conjunction with the memory,execute a photo service provided to enable automatic grouping basedhandling of similar photos.

Process 800 begins with operation 810, where a plurality of photos takenwithin a predefined period of time or of a similar scene may be receivedat a photo service. The photo service may analyze the plurality ofphotos based on a capture time, facial features, a backgroundcomposition, and a color composition at operation 820. At operation 830,a subset of the plurality of photos may be grouped as a stack based onapplying a threshold to analysis results.

At operation 840, lire photo service may select one of the photos m thestack as a representative photo based on a quality threshold, andprovide the stack to be displayed at operation 850 in a collapsed formatwith the representative photo on top using one or more visual indicatorsassociated with the stack.

The operations included in process 800 are for illustration purposes.Automatic grouping based handling of similar photos may be implementedby similar processes with fewer or additional steps, as well as indifferent order of operations using the principles described herein. Theoperations described herein may be executed by one or more processorsoperated on one or more computing devices, one or more processor cores,specialized processing devices, and/or general purpose processors, amongother examples.

According to some examples, a method to provide automatic grouping basedhandling of similar photos is described. The method may includereceiving a plurality of photos taken within a predefined period of timeor of a similar scene; analyzing the plurality of photos based on acapture time, facial features, a background composition, and a colorcomposition; grouping a subset of the plurality of photos as a stackbased on applying a threshold to analysis results; selecting one of thephotos in the stack as a representative photo based on a qualitythreshold; and enabling display of the stack in a collapsed format withthe representative photo on top using one or more visual indicatorsassociated with the stack.

According to some examples, a means for providing automatic groupingbased handling of similar photos is described. The means may include ameans for receiving a plurality of photos taken within a predefinedperiod of time or of a similar scene; a means for analyzing theplurality of photos based on a capture time, facial features, abackground composition, and a color composition; a means for grouping asubset of the plurality of photos as a stack based on applying athreshold to analysis results; a means for selecting one of the photosin the stack as a representative photo based on a quality threshold; anda means for enabling display of the stack in a collapsed format with therepresentative photo on top using one or more visual indicatorsassociated with the stack.

According to other examples, the method may further include enablingdisplay of context based menus of commands associated with group levelor individual photo level actions based on a display mode of the slack.The group level actions may include unstack, delete all, edit group,share representative photo, share all, or add group to album. Theindividual photo level actions may include set a selected photo as therepresentative photo, remove the selected photo from the stack, deletethe selected photo, edit the selected photo, share the selected photo,or add the selected photo to album. The method may also include enablingthe display of the context based menus of commands as one of a fixeduser interface command bar and a dynamically located pop-up menu.

According to further examples, the visual indicators may include one ormore of textual, graphic, coloring, shading, and highlightingindicators. The method may also include indicating a number of photos inthe stack through the visual indicators and/or indicating a thumbnail ofthe representative photo as representing the stack through the visualindicators. The method may yet include determining a person of interestwithin a group of people in the plurality of photos; and analyzing thefacial features of the person of interest for grouping purposes. Themethod may also include determining a group of people in the pluralityof photos; analyzing the facial features of every person in the group ofpeople; and averaging values assigned to analysis results of the facialfeatures.

According to other examples, a server-to execute a photo serviceconfigured to provide automatic grouping based handling of similarphotos is described. The server may include a communication interfaceconfigured to facilitate communication between the photo service and afirst device; a memory configured to store instructions; and one or moreprocessors coupled to lire memory. The one or more processors, inconjunction with the instructions stored in the memory, may beconfigured to receive a plurality of photos from the first device takenwithin a predefined period of time or of a similar scene; analyze theplurality of photos based on a capture time, facial features, abackground composition, and a color composition; group a subset of theplurality of photos as a stack based on applying a threshold to analysisresults; select one of the photos in the stack as a representative photobased on a quality threshold; and provide the stack to be displayed toone of the first device and a second device in a collapsed format withthe representative photo on top using one or more visual indicatorsassociated with the stack.

According to some examples, the one or more processors may be furtherconfigured to enable display of the stack on one of the first device andthe second device as a single photo among other photos with at least onevisual indicator indicating the single photo as representing the stack.The single photo may be a thumbnail of the representative photo. The oneor more processors may also be configured to enable expansion of thestack to display the subset of the plurality of photos by creating spaceamong the other photos on one of the first device and the second device.The first device may be a digital camera and the second device may beone of a handheld, desktop, laptop, and wearable computing device. Thefirst device and the second device may be a same computing device.

According to further examples, a computer readable memory device withinstructions stored thereon to provide automatic grouping based handlingof similar photos is described. The instructions may include receiving aplurality of photos taken within a predefined period of time or of asimilar scene; analyzing the plurality of photos based on a capturetime, facial features, a background composition, and a colorcomposition; grouping a subset of the plurality of photos as a stackbased on applying a difference threshold to analysis results; selectingone of the photos in the stack as a representative photo based on aquality threshold; and enabling display of the stack in a collapsedformat with the representative photo on top using one or more visualindicators associated with the stack, where the visual indicatorsinclude one or more of textual, graphic, coloring, shading, andhighlighting indicators configured to indicate one or more of athumbnail of the representative photo as representing the stack and anumber of photos in the stack.

According to other examples, the instructions may further includedetermining a difference metric based on analysis of the capture time,the facial features, the background composition, and the colorcomposition; and comparing the metric to the difference threshold. Theinstructions may also include selecting the representative photo basedon comparing a quality metric derived from an analysis of the facialfeatures, the background composition, and the color composition of thesubset of the plurality of photos; and storing a difference metric and aquality metric as metadata with the stack.

The above specification, examples and data provide a completedescription of the manufacture and use of the composition of theembodiments. Although the subject matter has been described in languagespecific to structural features and/or methodological acts, it is to beunderstood that the subject matter defined in the appended claims is notnecessarily limited to the specific features or acts described above.Rather, the specific features and acts described above are disclosed asexample forms of implementing the claims and embodiments.

1-20. (canceled)
 21. A method performed by a computing device, themethod comprising: performing image processing on a plurality of photosto identify one or more facial features; analyzing the plurality ofphotos to obtain analysis results, the analyzing being based at least onthe one or more facial features and one or more of capture times,background compositions, or color compositions of the plurality ofphotos; grouping a subset of the plurality of photos as a stack based atleast on the analysis results; designating a representative photo forthe stack; and outputting the representative photo for the stack. 22.The method of claim 21, further comprising: performing image processingon the plurality of photos to identify one or more backgroundcomposition features reflecting the background compositions, wherein theanalyzing is further based at least on the one or more backgroundcomposition features.
 23. The method of claim 21, further comprising:performing image processing on the plurality of photos to identify oneor more color composition features reflecting the color compositions,wherein the analyzing is further based at least on the one or more colorcomposition features.
 24. The method of claim 21, further comprising:receiving input directed to the representative photo; and outputting oneor more other photos of the subset in response to the input.
 25. Themethod of claim 24, wherein the outputting the one or more other photosof the subset comprises displaying the one or more other photos of thesubset in a horizontal row beneath the representative photo.
 26. Themethod of claim 25, wherein the outputting further comprises displayingunrelated photos in another horizontal row below the horizontal row. 27.The method of claim 21, wherein designating the representative photocomprises selecting one of the photos of the subset as therepresentative photo.
 28. The method of claim 27, wherein designatingthe representative photo comprises evaluating image quality of thephotos of the subset.
 29. The method of claim 21, wherein the pluralityof photos are not taken in a burst mode.
 30. A computing devicecomprising: a processor; and a volatile or nonvolatile storage mediastoring computer-readable instructions which, when executed by theprocessor, cause the processor to: perform image processing on aplurality of photos to identify one or more background compositionfeatures; analyze the plurality of photos to obtain analysis results,the analysis results being based at least on the one or more backgroundcomposition features and one or more of capture times, faces, or colorcompositions of the plurality of photos; group a subset of the pluralityof photos as a stack based at least on the analysis results; designate arepresentative photo for the stack; and output the representative photofor the stack.
 31. The computing device of claim 30, wherein thecomputer-readable instructions, when executed by the processor, causethe processor to: perform image processing on the plurality of photos toidentify one or more facial features reflecting the faces; perform imageprocessing on the plurality of photos to identify one or more colorcomposition features reflecting the color compositions; and analyze theplurality of photos based at least on the one or more backgroundcomposition features, the one or more facial features, and the one ormore color composition features.
 32. The computing device of claim 31,wherein the computer-readable instructions, when executed by theprocessor, cause the processor to: select the plurality of photos foranalysis based at least on the plurality of photos having been capturedwithin a predefined period of time.
 33. The computing device of claim31, wherein the computer-readable instructions, when executed by theprocessor, cause the processor to: select the plurality of photos foranalysis based at least on the plurality of photos including similarscenes.
 34. The computing device of claim 31, wherein the plurality ofphotos are originally captured by a camera in individual mode.
 35. Thecomputing device of claim 30, wherein the computer-readableinstructions, when executed by the processor, cause the processor to:provide a menu to perform one or more operations collectively on all ofthe photos in the stack.
 36. The computing device of claim 35, the oneor more operations including a deletion operation.
 37. The computingdevice of claim 35, the one or more operations including a sharingoperation.
 38. The computing device of claim 30, wherein therepresentative photo is output by displaying the representative photolocally on the computing device.
 39. The computing device of claim 30,provided as a server, wherein the computer-readable instructions, whenexecuted by the processor, cause the processor to: receive the pluralityof photos over a network from a computing device; and provide the stackto over the network to the computing device.
 40. A volatile ornonvolatile storage media storing computer-readable instructions which,when executed by a processor, cause the processor to perform actscomprising: performing image processing on a plurality of photos toidentify one or more color composition features; analyzing the pluralityof photos to obtain analysis results, the analyzing being based at leaston the one or more color composition features and one or more of capturetimes, background compositions, or facial features of the plurality ofphotos; grouping a subset of the plurality of photos as a stack based atleast on the analysis results; designating a representative photo forthe stack; and outputting the representative photo for the stack.